基于协作过算法的大数据搜索在跨境电子商务产品推中的应用.
1School of Foreign Studies, Yiwu Industrial and Commercial College, Yiwu, 322000 China.
Soft computing
|June 26, 2023
概括
本研究介绍了跨境电子商务大数据搜索的协作过算法. 它通过结合用户偏好和加权标签来增强产品建议,以改善决策.
科学领域:
- 计算机科学 计算机科学
- 电子商务 技术 技术 电子商务
- 数据科学数据科学数据科学
背景情况:
- 跨境电子商务正在迅速扩大,导致大量数据增长.
- 现有的大数据搜索系统与不准确的用户概况和低于最佳的产品建议作斗争.
- 越来越多的信息量使用户的决策过程变得复杂.
研究的目的:
- 为跨境电子商务平台开发一个改进的大数据搜索系统.
- 提高产品建议的准确性和相关性.
- 解决大数据集在用户决策支持中所带来的挑战.
主要方法:
- 实施一个大数据搜索系统,利用一个协作过算法.
- 构建用户矩阵标签,量化新用户偏好.
- 将权重概念集成到对算法输入的用户偏好标签中.
主要成果:
- 拟议的协作过算法有效地处理电子商务的大数据.
- 与现有方法相比,该系统展示了较好的产品推能力.
- 有权重的用户偏好标签提高了协作过算法的性能.
结论:
- 通过加权用户偏好标签增强的协作过是跨境电子商务大数据搜索的可行解决方案.
- 开发的系统可以通过提供更准确的产品建议来显著改善用户体验.
- 这种方法解决了当前电子商务大数据搜索和推系统的关键局限性.
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